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Updated: Apr 30, 2026

Virtual Reality Experiments with Physiological Measures
Published on: August 29, 2018
Multitasking Tug-of-War: Exploring the Impact of Task Modality, Task Load Level, and Task Load Type on Dual-Task
Mohamad El Iskandarani1, Matthew Bolton1, Sara Lu Riggs1
1University of Virginia, USA.
None:
ObjectiveThe present work investigates how task modality (visual, auditory), task load level (low or high), and task load type (target-distractor similarity, display rate) influence dual-task interference in virtual reality (VR).BackgroundDual-task interference is influenced by various factors including perceptual modality, where tasks that share the same modality may yield larger performance decrements than tasks that do not. Task load (i.e., level and type) can also reduce performance in one or both tasks. However, the interaction between these factors in immersive environments like VR is still unclear.MethodParticipants performed a: (a) visual tracking task, (b) visual/auditory detection task, or (c) both concurrently in two different experiments. In Experiment 1, visual tracking load was manipulated via increasing target-distractor similarity, while detection load was manipulated via increasing display rate. In Experiment 2, detection load was manipulated by increasing target-distractor similarity.ResultsIn Experiment 1, higher detection task loads induced greater dual-task costs (DTC) in the detection task regardless of task modality, whereas tracking task DTC was not influenced by higher task loads. In Experiment 2, higher detection task loads induced greater DTC in the detection task only when it was presented visually.ConclusionThe findings suggest that tasks presented in the same modality may experience greater dual-task interference in one or both tasks depending on the task load level and type.ApplicationThese findings can inform the design of multimodal interfaces in complex multitasking environments like military operations or emergency response where minimizing dual-task interference at varying workloads is crucial.
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